Histogram Analysis Comparison of Monoexponential, Advanced Diffusion-Weighted Imaging, and Dynamic Contrast-Enhanced MRI for Differentiating Borderline From Malignant Epithelial Ovarian Tumors.

The accurate preoperative differentiation between borderline and malignant epithelial ovarian tumors (BEOTs vs. MEOTs) is crucial for determining the proper surgical strategy and improving the patient's postoperative quality of life. Several diffusion and perfusion MRI technologies are valuable for the differentiation; however, which is the best remains unclear. To compare the whole solid-tumor volume histogram analysis of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced MRI (DCE-MRI) in the differentiation of BEOTs vs. MEOTs and to identify the correlations between the perfusion parameters from IVIM and DCE-MRI. Retrospective. Twenty patients with BEOTs and 42 patients with MEOTs. 1.5T/DWI, DKI, and IVIM models fitting from 13 different b factors and 40 phases DCE-MRI. Histogram metrics were derived from the apparent diffusion coefficient (ADC), diffusion kurtosis (K), diffusion coefficient (Dk), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), volume transfer constant (Ktrans ), rate constant (kep ), and extravascular extracellular volume fraction (ve ). The Mann-Whitney U-test and receiver operating characteristic curve were used to determine the best histogram metrics and parameters. Multivariate logistic regression analysis was used to determine the best combined model for each two from the four technologies. Spearman's rank correlation was used to analyze the correlations between the IVIM and DCE-MRI parameters. ADC, D, Dk, and D* were significantly higher in BEOTs than in MEOTs (P < 0.05). K, Ktrans , kep , and ve were significantly lower in BEOTs than in MEOTs (P < 0.05). The 10th percentile of Dk was the most reliable single metric, with an area under the curve (AUC) of 0.921. Dk combined with Ktrans yielded the highest AUC of 0.950. A weak inverse correlation was found between D and Ktrans (r = -0.320, P = 0.025) and between D and kep (r = -0.267, P = 0.037). The 10th percentile of Dk was the most valuable metric and Dk combined with Ktrans had the best performance for differentiating BEOTs from MEOTs. There was no evident link between perfusion-related parameters derived from IVIM and DCE-MRI. 4 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:257-268.

He M ，Song Y ，Li H ，Lu J ，Li Y ，Duan S ，Qiang J ... -  《-》

Diffusion kurtosis imaging for differentiating borderline from malignant epithelial ovarian tumors: A correlation with Ki-67 expression.

To investigate the use of diffusion kurtosis imaging (DKI) in differentiating borderline from malignant epithelial ovarian tumors (MEOTs) and to correlate DKI parameters with Ki-67 expression. Fifty-two consecutive patients with epithelial ovarian tumors (17 borderline epithelial ovarian tumors, BEOTs; 35 MEOTs) were prospectively evaluated using DKI with b values of 0, 500, 1000, 1500, 2000, and 2500 s/mm2 and standard diffusion-weighted imaging (DWI) with b values of 0 and 1000 s/mm2 using a 1.5T magnetic resonance imaging (MRI) unit. The kurtosis (K) and diffusion coefficient (D) from DKI and apparent diffusion coefficient (ADC) from standard DWI were measured, compared, and correlated with Ki-67 expression between the two groups. Statistical analyses were performed using the Mann-Whitney U-test, receiver operating characteristic (ROC) curves, and Spearman's correlation. The K value was significantly lower in BEOTs than in MEOTs (0.55 ± 0.09 vs. 0.9 ± 0.2), while the D and ADC values were significantly higher in BEOTs than in MEOTs (2.27 ± 0.35 vs. 1.39 ± 0.37 and 1.72 ± 0.36 vs. 1.1 ± 0.25, respectively) (P < 0.001). For differentiating between BEOTs and MEOTs, the sensitivity, specificity, and accuracy were 88.2%, 94.3%, and 92.3% for K value; 88.2%, 91.4%, and 90.4% for D value; and 88.2%, 88.6%, and 88.5% for ADC value, respectively. However, there were no differences in the diagnostic performances among the three parameters above (K vs. ADC, P = 0.203; D vs. ADC, P = 0.148; K vs. D, P = 0.904). The K value was positively correlated with Ki-67 expression (r = 0.699), while the D and ADC values were negatively correlated with Ki-67 expression (r = -0.680, -0.665, respectively). Preliminary findings demonstrate that DKI is an alternative tool for differentiating BEOTs from MEOTs, and is correlated with Ki-67 expression. However, no added value is found for DKI compared with standard DWI. 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1499-1506.

Li HM ，Zhao SH ，Qiang JW ，Zhang GF ，Feng F ，Ma FH ，Li YA ，Gu WY ... -  《-》

Whole-tumor histogram analysis of monoexponential and advanced diffusion-weighted imaging for sinonasal malignant tumors: Correlations with histopathologic features.

The histopathological basis of monoexponential diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in the characterization of sinonasal malignant tumors is still unclear. To explore the correlations of histogram metrics from monoexponential DWI, IVIM, and DKI with histopathologic features in sinonasal malignant tumors. Retrospective. In all, 76 patients with sinonasal malignant tumors. Fourteen different b values (b = 0, 50, 100, 150, 200, 250, 300, 350, 400, 800, 1000, 1500, 2000, and 2500 sec/mm2 ) were used to perform different DWI models at 3.0T. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), diffusion kurtosis (K), and diffusion coefficient (Dk) maps. Histopathologic features, including nuclear, cytoplasmic, cellular, stromal fractions, and the nuclear-to-cytoplasmic (N/C) ratio, were measured. Spearman correlations and stepwise multiple linear regression analyses were performed to determine the correlations between histogram metrics and histopathologic features. ADC, Dk, and f histogram metrics showed significant correlations with investigated histopathologic features; D and K histogram metrics were significantly correlated with cellular, stromal, and nuclear fractions (all P < 0.05). Significant correlations between the 75th percentile of D and cytoplasmic fraction and between the kurtosis of K and the N/C ratio were observed (P < 0.05). The skewness of Dk, K, and the 75th percentile of D were independently associated with cellular and nuclear fractions; the skewness of Dk and K were independently associated with stromal fraction (P < 0.05). Monoexponential and advanced DWI histogram parameters were significantly correlated with histopathologic features in sinonasal malignancies. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:273-285.

Xiao Z ，Tang Z ，Zhang J ，Yang G ，Zeng W ，Luo J ，Song Y ，Zhang Z ... -  《-》

Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging to Early Detect Tissue Injury and Microcirculation Alteration in Hepatic Injury Induced by Intestinal Ischemia-Reperfusion in a Rat Model.

Intravoxel incoherent motion (IVIM) can provide quantitative information about water diffusion and perfusion that can be used to evaluate hepatic injury, but it has not been studied in hepatic injury induced by intestinal ischemia-reperfusion (IIR). Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) can provide perfusion data, but it is unclear whether it can provide useful information for assessing hepatic injury induced by IIR. To examine whether IVIM and DCE-MRI can detect early IIR-induced hepatic changes, and to evaluate the relationship between IVIM and DCE-derived parameters and biochemical indicators and histological scores. Prospective pre-clinical study. Forty-two male Sprague-Dawley rats. IVIM-diffusion-weighted imaging (DWI) using diffusion-weighted echo-planar imaging sequence and DCE-MRI using fast spoiled gradient recalled-based sequence at 3.0 T. All rats were randomly divided into the control group (Sham), the simple ischemia group, the ischemia-reperfusion (IR) group (IR1h, IR2h, IR3h, and IR4h) in a model of secondary hepatic injury caused by IIR, and IIR was induced by clamping the superior mesenteric artery for 60 minutes and then removing the vascular clamp. Advanced Workstation (AW) 4.6 was used to calculate the imaging parameters (apparent diffusion coefficient [ADC], true diffusion coefficient [D], perfusion-related diffusion [D* ] and volume fraction [f]) of IVIM. OmniKinetics (OK) software was used to calculate the DCE imaging parameters (Ktrans , Kep , and Ve ). Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were analyzed with an automatic biochemical analyzer. Superoxide dismutase (SOD) activity was assessed using the nitro-blue tetrazolium method. Malondialdehyde (MDA) was determined by thiobarbituric acid colorimetry. Histopathology was performed with hematoxylin and eosin staining. One-way analysis of variance (ANOVA) and Bonferroni post-hoc tests were used to analyze the imaging parameters and biochemical indicators among the different groups. Pearson correlation analysis was applied to determine the correlation between imaging parameters and biochemical indicators or histological score. ALT and MDA reached peak levels at IR4h, while SOD reached the minimum level at IR4h (all P < 0.05). ADC, D, D* , and f gradually decreased as reperfusion continued, and Ktrans and Ve gradually increased (all P < 0.05). The degrees of change for f and Ve were greater than those of other imaging parameters at IR1h (all P < 0.05). All groups showed good correlation between imaging parameters and SOD and MDA (r[ADC] = 0.615, -0.666, r[D] = 0.493, -0.612, r[D* ] = 0.607, -0.647, r[f] = 0.637, -0.682, r[Ktrans ] = -0.522, 0.500, r[Ve ] = -0.590, 0.665, respectively; all P < 0.05). However, the IR groups showed poor or no correlation between the imaging parameters and SOD and MDA (P [Ktrans and MDA] = 0.050, P [D and SOD] = 0.125, P [the remaining imaging parameters] < 0.05). All groups showed a positive correlation between histological score and Ktrans and Ve (r = 0.775, 0.874, all P < 0.05), and a negative correlation between histological score and ADC, D, f, and D* (r = -0.739, -0.821, -0.868, -0.841, respectively; all P < 0.05). For the IR groups, there was a positive correlation between histological score and Ktrans and Ve (r = 0.747, 0.802, all P < 0.05), and a negative correlation between histological score and ADC, D, f, and D* (r = -0.567, -0.712, -0.715, -0.779, respectively; all P < 0.05). The combined application of IVIM and DCE-MRI has the potential to be used as an imaging tool for monitoring IIR-induced hepatic histopathology. 1 TECHNICAL EFFICACY STAGE: 2.

Yang J ，Meng M ，Pan C ，Qian L ，Sun Y ，Shi H ，Shen Y ，Dou W ... -  《-》

Use of diffusion kurtosis imaging and quantitative dynamic contrast-enhanced MRI for the differentiation of breast tumors.

Breast MRI is a sensitive imaging technique to assess breast cancer but its effectiveness still remains to be improved. To evaluate the diagnostic performance of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and quantitative dynamic contrast-enhanced (DCE)-MRI in differentiating malignant from benign breast lesions independently or jointly and to explore whether correlations exist among these parameters. Retrospective. In all, 106 patients with breast lesions (47 malignant, 59 benign). DKI sequence with seven b values and quantitative DCE sequence on 3.0T MRI. Diffusion parameters (mean diffusivity [MD], mean diffusivity [MK], and apparent diffusion coefficient [ADC]) from DKI and DWI and perfusion parameters from DCE (Ktrans , kep , ve , and vp ) were calculated by two experienced radiologists after postprocessing. Disagreement between the two observers was resolved by consensus. The parameters in benign and malignant lesions were compared by Student's t-test. The diagnostic performances of DKI and quantitative DCE, either alone or in combination, were evaluated by receiver operating characteristic (ROC) analysis. The Spearman correlation test was used to evaluate correlations among the diffusion parameters and perfusion parameters. MK, MD, ADC, Ktrans , and kep values were significantly different between breast cancer and benign lesions (P < 0.05). MK from DKI demonstrated the highest AUC of 0.849, which is significantly higher than ADC derived from conventional DWI (z = 3.345, P = 0.0008). The specificity of DCE-MRI-derived parameters was improved when combining diffusion parameters, such as ADC and MK. The highest diagnostic specificity (93.2%) was obtained when kep and ADC were combined. kep was correlated moderately positively with MK (r = 0.516) and moderately negatively with MD (r = -0.527). Ktrans was weakly positively correlated with MK with an r of 0.398 and weakly negatively correlated with MD with an r of -0.450. DKI is more valuable than conventional DWI in distinguishing between benign and malignant breast lesions. DKI exhibits promise as a quantitative technique to augment quantitative DCE-MRI. Diffusion parameters derived from DKI were statistically correlated with perfusion parameters from quantitative DCE-MRI. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1358-1366.

Li T ，Yu T ，Li L ，Lu L ，Zhuo Y ，Lian J ，Xiong Y ，Kong D ，Li K ... -  《-》